Jean-François Spinella

Integration of High-Resolution Methylome and Transcriptome Analyses to Dissect Epigenomic Changes in Childhood Acute Lymphoblastic Leukemia

B-cell precursor acute lymphoblastic leukemia (pre-B ALL) is the most common pediatric cancer. Although the genetic determinants underlying disease onset remain unclear, epigenetic modifications including DNA methylation are suggested to contribute significantly to leukemogenesis. Using the Illumina 450K array, we assessed DNA methylation in matched tumor-normal samples of 46 childhood patients with pre-B ALL, extending single CpG-site resolution analysis of the pre-B ALL methylome beyond CpG-islands (CGI). Unsupervised hierarchical clustering of CpG-site neighborhood, gene, or microRNA (miRNA) gene-associated methylation levels separated the tumor cohort according to major pre-B ALL subtypes, and methylation in CGIs, CGI shores, and in regions around the transcription start site was found to significantly correlate with transcript expression. Focusing on samples carrying the t(12;21) ETV6-RUNX1 fusion, we identified 119 subtype-specific high-confidence marker CpG-loci. Pathway analyses linked the CpG-loci-associated genes with hematopoiesis and cancer. Further integration with whole-transcriptome data showed the effects of methylation on expression of 17 potential drivers of leukemogenesis. Independent validation of array methylation and sequencing-derived transcript expression with Sequenom Epityper technology and real-time quantitative reverse transcriptase PCR, respectively, indicates more than 80% empirical accuracy of our genome-wide findings. In summary, genome-wide DNA methylation profiling enabled us to separate pre-B ALL according to major subtypes, to map epigenetic biomarkers specific for the t(12;21) subtype, and through a combined methylome and transcriptome approach to identify downstream effects on candidate drivers of leukemogenesis.

SNooPer: a machine learning-based method for somatic variant identification from low-pass next-generation sequencing

BackgroundNext-generation sequencing (NGS) allows unbiased, in-depth interrogation of cancer genomes. Many somatic variant callers have been developed yet accurate ascertainment of somatic variants remains a considerable challenge as evidenced by the varying mutation call rates and low concordance among callers. Statistical model-based algorithms that are currently available perform well under ideal scenarios, such as high sequencing depth, homogeneous tumor samples, high somatic variant allele frequency (VAF), but show limited performance with sub-optimal data such as low-pass whole-exome/genome sequencing data. While the goal of any cancer sequencing project is to identify a relevant, and limited, set of somatic variants for further sequence/functional validation, the inherently complex nature of cancer genomes combined with technical issues directly related to sequencing and alignment can affect either the specificity and/or sensitivity of most callers.ResultsFor these reasons, we developed SNooPer, a versatile machine learning approach that uses Random Forest classification models to accurately call somatic variants in low-depth sequencing data. SNooPer uses a subset of variant positions from the sequencing output for which the class, true variation or sequencing error, is known to train the data-specific model. Here, using a real dataset of 40 childhood acute lymphoblastic leukemia patients, we show how the SNooPer algorithm is not affected by low coverage or low VAFs, and can be used to reduce overall sequencing costs while maintaining high specificity and sensitivity to somatic variant calling. When compared to three benchmarked somatic callers, SNooPer demonstrated the best overall performance.ConclusionsWhile the goal of any cancer sequencing project is to identify a relevant, and limited, set of somatic variants for further sequence/functional validation, the inherently complex nature of cancer genomes combined with technical issues directly related to sequencing and alignment can affect either the specificity and/or sensitivity of most callers. The flexibility of SNooPer’s random forest protects against technical bias and systematic errors, and is appealing in that it does not rely on user-defined parameters. The code and user guide can be downloaded at https://sourceforge.net/projects/snooper/.

Whole-exome sequencing of a rare case of familial childhood acute lymphoblastic leukemia reveals putative predisposing mutations in Fanconi anemia genes

BackgroundAcute lymphoblastic leukemia (ALL) is the most common pediatric cancer. While the multi-step model of pediatric leukemogenesis suggests interplay between constitutional and somatic genomes, the role of inherited genetic variability remains largely undescribed. Nonsyndromic familial ALL, although extremely rare, provides the ideal setting to study inherited contributions to ALL. Toward this goal, we sequenced the exomes of a childhood ALL family consisting of mother, father and two non-twinned siblings diagnosed with concordant pre-B hyperdiploid ALL and previously shown to have inherited a rare form of PRDM9, a histone H3 methyltransferase involved in crossing-over at recombination hotspots and Holliday junctions. We postulated that inheritance of additional rare disadvantaging variants in predisposing cancer genes could affect genomic stability and lead to increased risk of hyperdiploid ALL within this family.MethodsWhole exomes were captured using Agilent’s SureSelect kit and sequenced on the Life Technologies SOLiD System. We applied a data reduction strategy to identify candidate variants shared by both affected siblings. Under a recessive disease model, we focused on rare non-synonymous or frame-shift variants in leukemia predisposing pathways.ResultsThough the family was nonsyndromic, we identified a combination of rare variants in Fanconi anemia (FA) genes FANCP/SLX4 (compound heterozygote - rs137976282/rs79842542) and FANCA (rs61753269) and a rare homozygous variant in the Holliday junction resolvase GEN1 (rs16981869). These variants, predicted to affect protein function, were previously identified in familial breast cancer cases. Based on our in-house database of 369 childhood ALL exomes, the sibs were the only patients to carry this particularly rare combination and only a single hyperdiploid patient was heterozygote at both FANCP/SLX4 positions, while no FANCA variant allele carriers were identified. FANCA is the most commonly mutated gene in FA and is essential for resolving DNA interstrand cross-links during replication. FANCP/SLX4 and GEN1 are involved in the cleavage of Holliday junctions and their mutated forms, in combination with the rare allele of PRDM9, could alter Holliday junction resolution leading to nondisjunction of chromosomes and segregation defects.ConclusionTaken together, these results suggest that concomitant inheritance of rare variants in FANCA, FANCP/SLX4 and GEN1 on the specific genetic background of this familial case, could lead to increased genomic instability, hematopoietic dysfunction, and higher risk of childhood leukemia.

Genomic characterization of pediatric T-cell acute lymphoblastic leukemia reveals novel recurrent driver mutations

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy with variable prognosis. It represents 15% of diagnosed pediatric ALL cases and has a threefold higher incidence among males. Many recurrent alterations have been identified and help define molecular subgroups of T-ALL, however the full range of events involved in driving transformation remain to be defined. Using an integrative approach combining genomic and transcriptomic data, we molecularly characterized 30 pediatric T-ALLs and identified common recurrent T-ALL targets such as FBXW7, JAK1, JAK3, PHF6, KDM6A and NOTCH1 as well as novel candidate T-ALL driver mutations including the p.R35L missense mutation in splicesome factor U2AF1 found in 3 patients and loss of function mutations in the X-linked tumor suppressor genes MED12 (frameshit mutation p.V167fs, splice site mutation g.chrX:70339329T>C, missense mutation p.R1989H) and USP9X (nonsense mutation p.Q117*). In vitro functional studies further supported the putative role of these novel T-ALL genes in driving transformation. U2AF1 p.R35L was shown to induce aberrant splicing of downstream target genes, and shRNA knockdown of MED12 and USP9X was shown to confer resistance to apoptosis following T-ALL relevant chemotherapy drug treatment in Jurkat leukemia cells. Interestingly, nearly 60% of novel candidate driver events were identified among immature T-ALL cases, highlighting the underlying genomic complexity of pediatric T-ALL, and the need for larger integrative studies to decipher the mechanisms that contribute to its various subtypes and provide opportunities to refine patient stratification and treatment.

CLIC5: a novel ETV6 target gene in childhood acute lymphoblastic leukemia

The most common rearrangement in childhood precursor B-cell acute lymphoblastic leukemia is the t(12;21)(p13;q22) translocation resulting in the ETV6-AML1 fusion gene. A frequent concomitant event is the loss of the residual ETV6 allele suggesting a critical role for the ETV6 transcriptional repressor in the etiology of this cancer. However, the precise mechanism through which loss of functional ETV6 contributes to disease pathogenesis is still unclear. To investigate the impact of ETV6 loss on the transcriptional network and to identify new transcriptional targets of ETV6, we used whole transcriptome analysis of both pre-B leukemic cell lines and patients combined with chromatin immunoprecipitation. Using this integrative approach, we identified 4 novel direct ETV6 target genes: CLIC5, BIRC7, ANGPTL2 and WBP1L. To further evaluate the role of chloride intracellular channel protein CLIC5 in leukemogenesis, we generated cell lines overexpressing CLIC5 and demonstrated an increased resistance to hydrogen peroxide-induced apoptosis. We further described the implications of CLIC5’s ion channel activity in lysosomal-mediated cell death, possibly by modulating the function of the transferrin receptor with which it colocalizes intracellularly. For the first time, we showed that loss of ETV6 leads to significant overexpression of CLIC5, which in turn leads to decreased lysosome-mediated apoptosis. Our data suggest that heightened CLIC5 activity could promote a permissive environment for oxidative stress-induced DNA damage accumulation, and thereby contribute to leukemogenesis.

A novel somatic mutation in ACD induces telomere lengthening and apoptosis resistance in leukemia cells

BackgroundThe identification of oncogenic driver mutations has largely relied on the assumption that genes that exhibit more mutations than expected by chance are more likely to play an active role in tumorigenesis. Major cancer sequencing initiatives have therefore focused on recurrent mutations that are more likely to be drivers. However, in specific genetic contexts, low frequency mutations may also be capable of participating in oncogenic processes. Reliable strategies for identifying these rare or even patient-specific (private) mutations are needed in order to elucidate more personalized approaches to cancer diagnosis and treatment.MethodsHere we performed whole-exome sequencing on three cases of childhood pre-B acute lymphoblastic leukemia (cALL), representing three cytogenetically-defined subgroups (high hyperdiploid, t(12;21) translocation, and cytogenetically normal). We applied a data reduction strategy to identify both common and rare/private somatic events with high functional potential. Top-ranked candidate mutations were subsequently validated at high sequencing depth on an independent platform and in vitro expression assays were performed to evaluate the impact of identified mutations on cell growth and survival.ResultsWe identified 6 putatively damaging non-synonymous somatic mutations among the three cALL patients. Three of these mutations were well-characterized common cALL mutations involved in constitutive activation of the mitogen-activated protein kinase pathway (FLT3 p.D835Y, NRAS p.G13D, BRAF p.G466A). The remaining three patient-specific mutations (ACD p.G223V, DOT1L p.V114F, HCFC1 p.Y103H) were novel mutations previously undescribed in public cancer databases. Cytotoxicity assays demonstrated a protective effect of the ACD p.G223V mutation against apoptosis in leukemia cells. ACD plays a key role in protecting telomeres and recruiting telomerase. Using a telomere restriction fragment assay, we also showed that this novel mutation in ACD leads to increased telomere length in leukemia cells.ConclusionThis study identified ACD as a novel gene involved in cALL and points to a functional role for ACD in enhancing leukemia cell survival. These results highlight the importance of rare/private somatic mutations in understanding cALL etiology, even within well-characterized molecular subgroups.

Mutational dynamics of early and late relapsed childhood ALL: rapid clonal expansion and long-term dormancy

Childhood acute lymphoblastic leukemia (cALL) is the most frequent pediatric cancer. Refractory/relapsed cALL presents a survival rate of ∼45% and is still one of the leading causes of death by disease among children. Mechanisms, such as clonal competition and evolutionary adaptation, govern treatment resistance. However, the underlying clonal dynamics leading to multiple relapses and differentiating early (<36 months postdiagnosis) from late relapse events remain elusive. Here, we use an integrative genome-based analysis combined with serial sampling of relapsed tumors (from primary tumor to ≤4 relapse events) from 19 pre-B-cell cALL patients (8 early and 11 late relapses) to assess the fitness of somatic mutations and infer their ancestral relationships. By quantifying both general clonal dynamics and newly acquired subclonal diversity, we show that 2 distinct evolutionary patterns govern early and late relapse: on one hand, a highly dynamic pattern, sustained by a putative defect of DNA repair processes, illustrating the quick emergence of fitter clones, and on the other hand, a quasi-inert evolution pattern, suggesting the escape from dormancy of leukemia stem cells likely spared from initial cytoreductive therapy. These results offer new insights into cALL relapse mechanisms and highlight the pressing need for adapted treatment strategies to circumvent resistance mechanisms.

Characterization of the microDNA through the response to chemotherapeutics in lymphoblastoid cell lines

Recently, a new class of extrachromosomal circular DNA, called microDNA, was identified. They are on average 100 to 400 bp long and are derived from unique non-repetitive genomic regions with high gene density. MicroDNAs are thought to arise from DNA breaks associated with RNA metabolism or replication slippage. Given the paucity of information on this entirely novel phenomenon, we aimed to get an additional insight into microDNA features by performing the microDNA analysis in 20 independent human lymphoblastoid cell lines (LCLs) prior and after treatment with chemotherapeutic drugs. The results showed non-random genesis of microDNA clusters from the active regions of the genome. The size periodicity of 190 bp was observed, which matches DNA fragmentation typical for apoptotic cells. The chemotherapeutic drug-induced apoptosis of LCLs increased both number and size of clusters further suggesting that part of microDNAs could result from the programmed cell death. Interestingly, proportion of identified microDNA sequences has common loci of origin when compared between cell line experiments. While compatible with the original observation that microDNAs originate from a normal physiological process, obtained results imply complementary source of its production. Furthermore, non-random genesis of microDNAs depicted by redundancy between samples makes these entities possible candidates for new biomarker generation.

Joint genotype inference with germline and somatic mutations

The joint sequencing of related genomes has become an important means to discover rare variants. Normal-tumor genome pairs are routinely sequenced together to find somatic mutations and their associations with different cancers. Parental and sibling genomes reveal de novo germline mutations and inheritance patterns related to Mendelian diseases.Acute lymphoblastic leukemia (ALL) is the most common paediatric cancer and the leading cause of cancer-related death among children. With the aim of uncovering the full spectrum of germline and somatic genetic alterations in childhood ALL genomes, we conducted whole-exome re-sequencing on a unique cohort of over 120 exomes of childhood ALL quartets, each comprising a patients tumor and matched-normal material, and DNA from both parents. We developed a general probabilistic model for such quartet sequencing reads mapped to the reference human genome. The model is used to infer joint genotypes at homologous loci across a normal-tumor genome pair and two parental genomes.We describe the algorithms and data structures for genotype inference, model parameter training. We implemented the methods in an open-source software package (QUAD GT) that uses the standard file formats of the 1000 Genomes Project. Our methods utility is illustrated on quartets from the ALL cohort.

Whole-exome sequencing identified genetic risk factors for asparaginase-related complications in childhood ALL patients

Allergy, pancreatitis and thrombosis are common side-effects of childhood acute lymphoblastic leukemia (ALL) treatment that are associated with the use of asparaginase (ASNase), a key component in most ALL treatment protocols. Starting with predicted functional germline variants obtained through whole-exome sequencing (WES) data of the Quebec childhood ALL cohort we performed exome-wide association studies with ASNase-related toxicities. A subset of top-ranking variants was further confirmed by genotyping (N=302) followed by validation in an independent replication group (N=282); except for thrombosis which was not available for that dataset. SNPs in 12 genes were associated with ASNase complications in discovery cohort including 3 that were associated with allergy, 3 with pancreatitis and 6 with thrombosis. The risk was further increased through combined SNPs effect (p≤0.002), suggesting synergistic interactions between the SNPs identified in each of the studied toxicities. Interestingly, rs3809849 in the MYBBP1A gene was associated with allergy (p= 0.0006), pancreatitis (p=0.002), thrombosis (p=0.02), event-free survival (p=0.02) and overall survival (p=0.003). Furthermore, rs11556218 in IL16 and rs34708521 in SPEF2 were both associated with thrombosis (p=0.01 and p=0.03, respectively) and pancreatitis (p=0.02). The association of SNPs in MYBBP1A, SPEF2 and IL16 geneswith pancreatitis was replicated in the validation cohort (p ≤0.05) as well as in combined cohort (p=0.0003, p=0.008 and p=0.02, respectively). The synergistic effect of combining risk loci had the highest power to predict the development of pancreatitis in both cohorts and was further potentiated in the combined cohort (p=1×10-8). The present work demonstrates that using WES data is a successful “hypothesis-free” strategy for identifying significant genetic markers modulating the effect of the treatment in childhood ALL.